code: def get_config(run_local: str = "") -> ml_collections.ConfigDict:
      """Returns the experiment configuration."""
      run_local_str = run_local
  
      config = ml_collections.ConfigDict()
  
      config.trainer_name = "visual_text_trainer"
  
      # config.num_training_epochs = 32
      config.num_training_steps = 100000
  
      config.optimizer = "radamw"
      config.optimizer_configs = ml_collections.ConfigDict()
      config.optimizer_configs.weight_decay = 0.01
      config.optimizer_configs.skip_scale_and_bias_regularization = True
      config.optimizer_configs.gradient_centralization = False
      config.optimizer_configs.lookahead = False
      config.optimizer_configs.lookahead_sync_period = 5
      config.optimizer_configs.lookahead_slow_step_size = 0.5
      config.optimizer_configs.params_to_freeze = ()
      config.max_grad_norm = 0.5
      config.label_smoothing = None  # TODO(sacastro): unused.
      config.temperature = 0.01
      config.fit_temperature = False  # TODO(sacastro): unused.
  
      config.lr_configs = ml_collections.ConfigDict()
      config.lr_configs.learning_rate_schedule = "compound"
      config.lr_configs.factors = (
          "linear_warmup * constant * cosine_decay"
      )
      config.lr_configs.warmup_steps = 0.1
      config.lr_configs.steps_per_cycle = 1.0
      config.lr_configs.base_learning_rate = 5e-4
  
      config.log_summary_steps = 20
      # config.log_eval_steps = 100
      config.eval_while_training = False
      config.checkpoint_steps = 200
  
      # The following inherit configs from CLIP, but we're going to use them in a
      # way that we won't use the model's properties.
      config.evaluation_configs = (
          mixin_hmdb51.get_config(run_local_str),
          mixin_imagenet.get_config(run_local_str),
          mixin_kinetics400.get_config(run_local_str),
          mixin_kinetics600.get_config(run_local_str),
          mixin_kinetics700.get_config(run_local_str),
          mixin_msr_vtt.get_config(run_local_str),
          mixin_ucf101.get_config(run_local_str),
          mixin_youcook2.get_config(run_local_str),
      )
  
      return config
  
file_path: scenic/scenic/projects/lang4video/configs/train/mixin.py
imports: import ml_collections
  from scenic.projects.lang4video.configs.datasets import mixin_hmdb51
  from scenic.projects.lang4video.configs.datasets import mixin_imagenet
  from scenic.projects.lang4video.configs.datasets import mixin_kinetics400
  from scenic.projects.lang4video.configs.datasets import mixin_kinetics600
  from scenic.projects.lang4video.configs.datasets import mixin_kinetics700
  from scenic.projects.lang4video.configs.datasets import mixin_msr_vtt
  from scenic.projects.lang4video.configs.datasets import mixin_ucf101
  from scenic.projects.lang4video.configs.datasets import mixin_youcook2
label_desc: Use image node_id 1 for calling a global function with example usage: get_config(run_local) and returns: config